David Hugh-Jones

Wednesday, 28 February 2018

It is time to come out. I am writing a book. When I tell this to senior academics, they wish me "Good luck," and their eyes gain a mysterious, troubled look. Writing books is not what economists do.

Here is a self-justifying sketch of the relationship between social science and its historical setting.

Think of the possible states of society as a multi-dimensional space, each dimension corresponding to a variable: the growth rate, inequality, the price of corn, the prevalence of opiate addiction and so on. Different societies or parts of society – Kansas and New York, Denmark and Greece, or South London and North Oxford – are at different points in the space.

Nearby societies are at different points in a many-dimensional space

Some exogenous variables are like the weather: they change naturally, but we cannot change them. Others are policy variables, in the broadest sense that they can be affected by collective human choices. The optimal value of the policy variables depends in on the value of the exogenous variables. Social science involves working out how our welfare depends on the policy and exogenous variables.

At settled times in history, society appears static. Expected changes in the exogenous variables are small, and welfare appears high, suggesting that policy variables are about right. In this state, social science involves looking nearby in the social space – probably within the convex hull formed by different existing parts of our society. This gives us lots of data.

Economists talk about "looking for your keys under the street light". The idea is that your keys, if you have lost them, are no more likely to be lying under the street light than elsewhere; but it makes sense to look under the street light, rather than in the dark where you won't see them anyway.

In settled times, we look under the street light. Prestigious social science involves careful empirical work, leveraging the available data to recommend incremental policy changes. Think of Esther Duflo and the economist as an engineer, or, as Keynes once wistfully suggested, a modest profession like dentistry.

Social science in settled times: looking for small changes within the convex hull* of what is known[* the shape shown is not quite convex, but eh.]

Other times in history are times of turbulence, of fast change and widespread dissatisfaction with the status quo. Expected changes in exogenous variables are large, or social welfare appears low, suggesting that we need large changes in policy variables.

In turbulent times, we need to explore remote points in the policy space, beyond the convex hull of what is known. Social science involves bold steps of imagination and deep theoretical examination of current and possible structures. Think of Marx and what Joan Robinson called his intellectual "seven-league boots", striding forward over trivial details. Or think of the public choice movement of the 1970s, which looked at the foundations of political constitutions. In fact, we need to "look for our keys under the lightning" –
flashes of insight which illuminate the whole landscape and point to big
possible changes.

Social science in turbulent times: looking for keys under the lightning.

Today we are living in turbulent times. The economy is changing fast as the centre of the world moves East. Politics, driven by voter dissatisfaction, is just as fast-moving and less predictable.

Of course, it is arrogant to assume that you can produce a bolt of intellectual lightning! But if the premium is on lightning, then it may be worth trying.

This is why I am ignoring my senior colleagues' troubled looks, and writing a book.

Sunday, 25 February 2018

Those politicians that grasp this new reality – Leftists like Corbyn, nationalists like Trump, centrists like Macron – win elections. Those that don’t, don’t.

Let's stay on this topic. I got an email from Brandon Lewis yesterday. Brandon Lewis is the new broom at Central Office, part of his remit being to bring social media pizzazz to match Momentum.

Dear David,

What's up, Brandon?

With your support, we’re shaping the future of Britain. But Labour want to stop our progress.

Oh dear! That sounds generically bad.

That’s why the Prime Minister wrote to you, David.

And so it goes on. I'm not saying it was necessarily written by a smart-suited young person in marketing. It seems that way, but who knows? Maybe Brandon – or as I call him, the B-Dogg – penned and sent it himself, with all the friendly personal touches.

So anyway, current wisdom runs that we can keep Theresa May, because she's still a bit ahead in the polls.

The internet has dramatically reduced the cost of
publishing. The market for news and opinion has gone from an
oligopoly to a classical free market, with many sellers and many buyers. What
before required industrial-scale machinery and a nationwide distribution
network can be done by anyone with a Facebook account.

By standard economic theory, that should be good
for consumers, providing more variety at lower cost. Mr Murray and Professor
Milanovic both broadly take this line. But long ago, Joseph Schumpeter argued
that monopoly could be better for innovation than free markets. A monopolist would
expect to reap all the dividends from investing in new techniques; in a free market, other sellers could and would steal your new ideas.

For news production on the internet, this argument applies
in spades. Newspapers always competed for the scoop and knew their rivals would
follow the story up the next day. (In the jargon, news is non-excludable.) The internet has exacerbated this: an article which took weeks of gumshoeing
to produce can be copied in a second – even if not literally copied and pasted,
its ideas can be taken. The traditional press is right to grumble that Google News and
Facebook are killing its business model.

The result is that analysis, which anyone with a brain can
produce, proliferates, but actual reporting, which costs time and money,
withers. And so, instead of scoops, we get front page news about cold weather
snaps. The extreme version of this is the Daily Express in the UK, which has
given up reporting as too costly, and fills its headlines with press releases
about heart disease drugs.

Unfortunately, modern democracies need the information gathered
by reporters much more than they need analyses from social scientists and pundits.

The end of the consensus

The old media firms were not neutral actors. To get
political news, the journalist asked his pals in the government for a juicy
story. In return, they expected favourable coverage. Different organs allied
with different political tribes, but when the elite as a whole agreed
on some view, challenges to that view went unheard.

This was the old-style social construction of reality. It
was certainly problematic. On the other hand, a consensus, even a biased one, provides society with the evidence base it needs to make collective
decisions, and common ground as the basis for constructive debate.

Clickbait

That has all gone. The Sun can no longer swing elections
with its headlines. A paper publishes a fishy story about Jeremy Corbyn meeting
a Czechoslovak spy – his rebuttal, on Youtube, gets a million views in a day.

Those politicians that grasp this new reality – Leftists
like Corbyn, nationalists like Trump, centrists like Macron – win elections.
Those that don’t, don’t.

Back in the day

Is this the democratic ideal realised? Nope: you can also
get a million hits by reporting fake news on Trump’s gorilla channel. News has
another quality: it is an experience good. What we buy are “stories”. We cannot
find out for ourselves which stories are real. The market failure this would normally
cause used to be mitigated by a journalistic outlet’s reputation. Broadsheet
newspapers were biased, but they left the really garbage stories to the
tabloids.

In a market with a million outlets, all copying each other,
this partial solution no longer works. As a result, we are drowning in
clickbait.

What solves public
goods problems?

The actors in this new reality will not be thoughtful
bloggers like Branko Milanovic. They will be states. States can control the
flow of information within their borders. They have the resources to produce fake
news, real news and everything in between. They can step in and solve the
public good problem. And they have the incentive to do so, because states need
to produce consensus supporting their actions.

Professor Milanovic occludes this point by describing
Al-Jazeera, Russia Today etc. as “foreigners” as against the “Anglo-American”
media. But this misses a distinction: Russia Today is directly an organ of the
Russian state. The New York Times is not.

Similarly, the fragmentation of the internet into national
borders is not a reactionary backlash against the new open world. It is part of
the same process. It is the obvious next step.

What is there to celebrate here? Yes, now the West knows
what it feels like. But when Radio Free Europe broadcast into the Soviet Bloc,
it was passing on the truth – at least some truth – from liberal democracies to
dissident citizens in some thoroughly nasty dictatorships. When RT broadcasts to
us, it gives us lies and conspiracy theories.

Western hegemony was often exercised brutally. Many liberals
and progressives, sensing its end, mistakenly infer that the rising powers –
Russia, China and their allies – will agree with their values better. This wishful
thinking will deserve the nasty surprise it gets.

Hobbits and hooligans

Douglas Murray celebrates the availability of new ideas that
challenge the consensus. I agree: I’m glad to read Jonathan Haidt or Nicholas
Christakis or Sam Harris.

We now have a free market in theories. Whereas before we all
had to buy the one theory, we now can pick the one we like best. Will the best
theory win?

The political theorist Jason Brennan describes three kinds
of citizens. There are hobbits, who like comfort and don’t want to be made to think; hooligans,
who gather evidence to support their preconceptions; and vulcans, rational
thinkers like Spock in Star Trek, who make ideal citizens because they inform
themselves impartially. Evidence from public opinion research provides the
kicker: basically, Vulcans don’t exist. There are only hobbits and hooligans. Jason
Brennan is skeptical about democracy.

Jordan Peterson seems like a good guy, and who is to
disagree with rules in his book like “Stand up straight with your shoulders
back”? Whether that is intellectually ground-breaking work, I am less sure. It
sounds an awful lot like Make Your Bed (author Admiral William H McRaven, US Navy,
retd). In general, there is a market right now for sensible, Victorian advice. What
Professor Peterson does seem to have is great charisma as a lecturer.

Intellectual progress requires more than the existence of competing
views. Those views must meet in reasoned debate, and the better argument must
win. The blogosphere, or Intellectual Dark Web or whatever, has not yet proved its
ability to generate this kind of progress. I hope it does. Meanwhile, it is
certainly nice to find intellectual allies, and the internet can provide that
for all of us.

Tuesday, 16 January 2018

Several of my political economy students found an article in the Journal of Public Policy (ungated link), on differences between the EU and US in lobbying. The key evidence, from interviews with corporate lobbyists, and doubtless obtained with great difficulty, is presented in this table:

Friday, 12 January 2018

When I mark essays, some types of comments come up repeatedly. I've written them down here. This lets me write down the best possible explanation once, instead of many times.

A note on style and marks
I will often correct your style, partly because I hate bad writing, and partly because one of the most important things you can learn is how to write well. Bad writing will not usually in itself give you lower marks: this is not an English course. But if bad writing is a sign of incoherent or vague ideas, then you will lose marks from that. Also, sometimes the writing is so bad that I literally do not know what the author is saying. See below, what mean?

ACADEMESE

Don’t try to write like an academic. Academics are lousy writers. Students pretending to be academics are even worse. Write as if you were explaining something to a friend, in the clearest and simplest way possible.

BAD: The work of X can keep such criticism at bay

BETTER: X’s work shows this criticism is wrong

BAD: Mill puts forth the notion of “…”

BETTER: Mill says “…”

(“such” is usually academese. Would you say “such criticism” in the pub? Sounds like such bullshit.)

BAD: it was the posit of a rational pursuit of goods which made analysis economic...

BAD: This is exemplary of a non-Pareto optimal realisation of policy.
BETTER: This is bad.

VERBOSE
Express each thought in as few words as possible. See also padding. Edit yourself. The delete key is your friend:

authoritarian regimes can be characterised by their willingness to bribe and use violence...

PADDING

Don’t pad out your word count. It’s obvious, and it won’t gain you marks, because I don’t want your essay to be long. I want it to be short, so I can finish marking the damn thing and do some research/go to the pub/take a candlelit bath with relaxing music.

FENCE-SITTING

Don’t use language to cover up uncertainty. Take a position, or honestly say you don’t know.

WHAT MEAN?

Your obscurity, fence-sitting or academese are so bad that I literally don’t understand what you are trying to say. Naturally, this is not good for your mark.

HUGE QUOTE
If you want to cite someone's paper, don't just quote great chunks of it: explain it in your own words. This makes your essay more coherent, and reassures me that you have understood what the other person is saying - not just copy-pasted it.

In the worst form of this disease, the whole essay is a patchwork of quotes held together by joining text. Why bother?

LAUNDRY LIST
An essay structure which lists a large number of arguments, without leading the reader from one to another, or explaining their role in the argument. More coherent than collection of paragraphs, but still hard to read.

RANDOM READING

Don’t just read papers/blog posts at random. Instead, start reading from what has been recommended. Put effort into searching for relevant papers - which aren’t necessarily ones with relevant-seeming titles. Try to work out whether a paper or book is important (citation counts help somewhat). The ability to find relevant papers is part of what we want you to learn.

Informal sources can be very useful but need to be consumed critically. If you only have blog posts and newspaper articles in your bibliography, then you probably have not read enough.

COLLECTION OF PARAGRAPHS
Individual paragraphs in your essay make sense, but they have no discernible relationship to one another. Each paragraph should build on the last, like stones in an arch:
Your work is more like:

COLLECTION OF SENTENCES
Like collection of paragraphs, but at a lower level. Individual sentences make sense, but I don't see how they relate to each other to form a coherent paragraph.

SECTION HEADINGS
These are a bad idea in a student essay. They're overkill for 2500 words, and they are often a sign that you don't have a single, clear thread of argument.

Tuesday, 5 December 2017

Some time ago I started seeing a psychotherapist, a
Jungian whom a friend had recommended. My excellent research assistant, a psychology PhD, was surprised
and scornful: “You realise that’s not real scientific psychology?”

Jung with pipe

She was right, of course. Jung is taken no more seriously
than Freud by modern psychologists. There’s no evidence that Jungian psychology
is practically effective either. Until the rise of cognitive behavioural
therapy, no school of therapy did better than any other in scientific trials,
or even better than just talking to a friend. With apologies to lay people, we can write this down in an
equation:

ATEJung = E[x | J = 1] – E[x | J = 0] = 0(1)

where x is mental health, E[x | J = 1] is the
expected level of a person’s mental health given a spell of Jungian
therapy, and E[x | J = 0] , is the expected level of their health after no treatment (or, say, after some more reasonable control, like talking to a friend). ATE is the Average Treatment Effect, the average effect on someone of having a Jungian therapist; equivalently, the difference between their health after Jungian
therapy and after the alternative.

But I stayed with my therapist all the same. My RA was right
to be shocked at such an unscientific attitude, no?

Some things about my guy seemed to differentiate him from
the average therapist, Jungian or not. He was extremely intelligent, thoughtful
and calm, and I’d developed a warm relationship with him. I felt that I’d
learned some things about myself and perhaps this was helping with my problems.

Here’s an equation for what matters to me:

TE[i] = (xi | J = 1) – (xi | J = 0)(2)

where TE[j] is the treatment effect on the psychological
health of unit j, the difference between their psychological health after seeing my
therapist and after the alternative; and i
represents myself. Equation (1) is just the average of equation (2), taken over
some appropriate population of patients and therapists. And if it is estimated right,
then your best guess of (2) for a random individual and a random therapist is
(1); in other words, by scientific standards Jungian therapy is useless.

But of course, I am not a random individual to myself, and
my therapist is also not randomly chosen. I know or believe many things
about me and him, which may lead me to a different estimate of (2). Some of
these will be the data of my own experience, others will be intuitions, or
perhaps what I’ve heard from my friend. It’s not obvious how I
should deal with the scientific information embodied in equation (1). It is not something I should just ignore, and it certainly comes out of a more
careful and objective process than my own scraps of intuition and gossip. But
that does not mean those scraps are worthless. Very little of the knowledge we live by day-to-day is scientific,
but we get by well enough.

In reality ignoring expertise means dismissing evidence, ignoring history and experience, and eventually denying straightforward facts.

With respect, this is one-sided, and even
arrogant and dangerous [1]. For instance, a person who worries that their job may be taken by a
migrant is not proved wrong by even theoretically perfect research showing that
immigration on average does not
reduce native employment [2]. Yes,
people can be misled by xenophobia or biased newspaper reporting. They may also
know specific things about their town, or their company, that researchers do
not. Those pieces of knowledge will not have been reached by careful scientific
experimentation. But decentralized, embodied information about specific
particular conditions is, among other things, what makes free markets work [3]. If all knowledge were expert knowledge, socialism would have outrun
capitalism.

Another point is specific to social science [4]. Humans live in
history, which is a river that you cannot step in twice: conditions are always
changing. What we are really interested in is the effect of certain policies in
future. But the only data we have is from the present and the past. Statisticians
understand the risk of extrapolating from the data – assuming that something’s
behaviour will remain predictable in conditions beyond the boundaries of what
one has so far observed [5]. Well, if time is a relevant variable, all social
science is extrapolation from the future to the past, and sometimes it fails. Relationships
that once held cease to do so, perhaps suddenly. To understand such a world,
the observer often has to make a choice: gather a respectably-sized sample,
perhaps reaching back far into the past [6]; or look
at what’s happening now and make a risky but relevant guess. Past averages; or
straws in the wind?

This often divides scientists from journalists. Social
scientists want to make well-founded generalizations and are trained to pay
little regard to journalists’ anecdotes. Journalists can legitimately retort that
they have a better instinct for what matters today. Neither side is always
right. I haven’t mentioned yet how little we truly know, perhaps
how little there is to know, about many vital matters of macro social science.
Put it this way: until they are a little better at predicting financial crises,
or the short run effects of Brexit, economists will fulminate in vain against journalists who don’t take their other predictions seriously.

The idea that everything to be known must be known by
scientific methods has a name: it is called scientism.
But scientism is not scientific.

Notes and references

[1] Incidentally, Professor Wren-Lewis gave the choice of Corbyn as Labour
leader as an example of ordinary people (Labour members) ignoring
expertise. I also used to think that was a bad idea for Labour. Neither of us look very expert now, do we?

[2] There’s a debate between George Borjas and others [1, 2]
on migration, which hinges, among other things, on how much to "borrow
strength" between different social groups, so as to predict one group's outcome from another's.

[4] This is why Professor Wren-Lewis is wrong to argue that ignoring experts on Brexit is "exactly equivalent to giving considerable publicity to a report from some climate change denial outfit". The equivalence is a bit looser than that.

[6] A good example is the very interesting dataset of financial crises collected by Reinhard and Rogoff for their book This Time Is Different. As their subtitle boasts, it reaches back through Eight Centuries of Financial Folly. It was certainly wrong to think the noughties' boom economy was different from any previous period, but it might reasonably be different from the conditions of the fourteenth century.

The “river you cannot step in twice” line comes from the Ancient Greek
philosopher Parmenides, who said that you cannot step in the same river twice.

Does discrimination contribute to the low percentage of dwarves in the high jump business? We designed an experiment to isolate discrimination’s potential effect. Without provision of information about candidates other than their appearance, those of full height are twice as likely to be hired for a high-jump task as dwarves…. We show that implicit stereotypes (as measured by the Implicit Association Test) predict not only the initial bias in beliefs but also the suboptimal updating of height-related expectations when performance-related information comes from the subjects themselves….

... it remains important from a policy point
of view to determine whether discrimination
exists and, if it does, what can be done to reduce it. For this reason,
we designed
an experiment in which supply-side
considerations did not apply (job candidates were chosen randomly and
could not opt out),
and thus possible differences in preference
could not lead to differences in performance quality (and thus
qualification).

We used a laboratory experiment in which subjects were “hired” to perform a jumping task: jumping over as many six inch poles as possible over a period of 4 min. We chose this task because of the strong evidence that it is performed equally well by dwarves and others. Nevertheless, it belongs to an area—high jumping — about which there is a pervasive stereotype that dwarves have inferior abilities….

Our results revealed a strong bias among subjects to hire tall people for the jumping task...

To clear something up straight away: no, I am not suggesting that women in maths are like dwarves in the high jump. The point of the experiment is to adjudicate whether there is really “unfair” or “irrational” bias against hiring women on the basis of maths competence. This is why the authors don’t just look at hiring rates in the real world. Instead they construct a task on which, by design, men and women perform equally. In the real world – this is the rhetoric – it would be hard to know whether employers are biased against women in science, or just have correct expectations about future performance. But in the lab we can conduct a fair test. Is not hiring women for maths like not hiring dwarves for the high jump? Or is it based on unfair prejudice? The latter, because women perform equally well on this task and still get discriminated against. Quoting from the real paper:

The effect of this [i.e. gender] stereotype on the hiring of women has been shown to be important in at least one field experiment. However, that study was unable to rule out the possibility that the decision to hire fewer women is the rational response to the lower effective quality of women’s future performance because of underinvestment by women caused by inferior career prospects or stereotype threat. For this reason, we used a laboratory experiment in which we could ensure there was no quality difference between sexes, because women performed equally well on the task in question, whether or not they were hired.

The problem is fairly obvious. If you are told to hire for a high jump task, you ain’t going to hire dwarves. If you think that men and women don’t perform equally well in maths, you won't hire women for a maths task. This will hold whether your belief is an irrational prejudice, a scientifically-validated fact of brain development, a sad but contingent truth of our society, or anything in between. Unless you are certain that the particular maths task is one which men and women do equally well at, you may as well follow your priors. Thus, the experiment doesn’t tell us which world we live in: the prejudice world, or the short-person-high-jump world. All it tells us is that subjects’ own experience of the maths task (they all took part in it, which to be fair is a plus point) was not enough to override their prior beliefs. That is irrational only against the benchmark of a genius who is omniscient about human behaviour.

The experiment could be improved by proving to subjects that men and women perform equally at the task in question, and then seeing whom they hired. But then it would become uninteresting for a different reason – the very probable null result would, again, be uninformative about what happens in real world hiring committees.

Summary: lab experiments may yet teach us a lot about gender differences and gender discrimination. But not this one.